**Role & seniority: ** Data Quality Engineer, 6–8 years experience

**Location & work type: ** Pan India, hiring suggests remote or location-flexible (work type not explicitly stated)

**Stack/tools: **

Python
PySpark
SQL
Playwright (test automation)
Cloud-enabled AI tools (AI-assisted testing/engineering)
Cloud platforms: Azure / AWS / GCP (preferred)

**Top 3 responsibilities: **

Design and implement data quality/validation frameworks (accuracy, completeness, consistency, integrity, reliability).
Build automated validation and regression/functional tests for large-scale data pipelines using Python/PySpark.
Develop and maintain automation frameworks using Playwright, and identify anomalies/root causes; monitor data quality metrics.

**Must-have skills: **

Hands-on Python and PySpark for data validation and testing
Data quality engineering experience (DQ/validation, ETL pipeline testing)
Playwright for automation
Strong SQL and data validation techniques
Ability to work with large datasets/distributed processing
Debugging/analytical problem-solving for upstream/downstream data issues
Cloud-based data engineering environment exposure
Collaboration with engineering/business stakeholders

**Nice-to-haves: **

Experience with Azure/AWS/GCP
CI/CD integration for automated testing
Strong communicati

Full Description

🚀 Hiring: Data Quality Engineer | Pan India We are looking for experienced Data Quality Engineers with strong expertise in Python, PySpark, Playwright, and Cloud-enabled AI tools to join our team. If you have a strong background in data quality engineering, automation, data validation, and testing large-scale data pipelines, we would love to connect with you! 🔹 Position Details

Role: Data Quality Engineer

Experience: 6–8 Years

Location: Pan India

Notice Period: Immediate Joiners to 30 Days

Key Skills: Python, PySpark, Playwright, Cloud-enabled AI Tools 🔹 Key Responsibilities Design, develop, and implement comprehensive data quality and validation frameworks. Build automated data validation and testing solutions using Python and PySpark. Perform data quality checks across large-scale datasets and data pipelines. Develop and maintain automation frameworks using Playwright. Validate data for accuracy, completeness, consistency, integrity, and reliability. Identify data anomalies, quality issues, and root causes across upstream and downstream systems. Automate regression, functional, and data validation testing. Leverage cloud-enabled AI tools to enhance testing, automation, and data quality processes. Collaborate closely with Data Engineers, Developers, Business Analysts, and other stakeholders. Monitor data quality metrics and support continuous improvement initiatives. Ensure reliable data delivery across cloud-based data platforms and applications. 🔹 Required Skills ✅ Strong hands-on experience with Python and PySpark ✅ Experience in Data Quality, Data Validation, ETL/Data Pipeline Testing ✅ Hands-on experience with Playwright for test automation ✅ Exposure to Cloud-enabled AI tools and AI-assisted engineering/testing ✅ Strong knowledge of SQL and data validation techniques ✅ Understanding of cloud-based data engineering environments ✅ Experience working with large datasets and distributed data processing ✅ Excellent analytical, debugging, and problem-solving skills 🔹 Preferred Qualifications 6–8 years of relevant IT experience with strong exposure to Data Quality Engineering. Experience with cloud platforms such as Azure, AWS, or GCP is advantageous. Knowledge of CI/CD and automated testing integration is preferred. Strong communication and stakeholder-management skills.